Inorganic Materials, Semiconductor & Superconductor Experts

Scientific assignment

Contribute experimental materials knowledge to an AI research program focused on materials science and the physical sciences. The work turns specialist judgment, procedures, measurements, and device knowledge into reliable training and evaluation data that can improve technical reasoning about materials, devices, and processes.

Core responsibilities

• Contribute expertise across synthesis, characterization, fabrication, and device physics.
• Review AI-generated scientific reasoning for technical errors, unsupported conclusions, and incomplete treatment of experimental constraints.
• Design and solve demanding problems within a defined scientific specialty.
• Rate and rank model outputs against stated scientific criteria, with concise written reasoning.
• Organize experimental procedures, characterization results, and process data into consistent, model-ready formats.
• Deliver accurate work within defined timelines.

Relevant expertise

Strong candidates have hands-on experience in at least one area: solid-state, solution, solvothermal, or sol-gel inorganic synthesis; superconducting materials; semiconductors; or advanced packaging. Materials and device characterization may include XRD, SEM, TEM, spectroscopy, and electrical or transport measurements. Experience with thin-film growth or device fabrication is useful, including MBE or epitaxy, MOCVD, CVD, sputtering, IBAD, etching, and clean-room microfabrication. An MS, PhD, or equivalent practical experience in materials science, chemistry, physics, or a related engineering field is expected, together with clear written English.

Engagement details

• Remote work based in the United States.
• Long-term, ongoing engagement.
• Up to 40 hours per week, with a minimum commitment of 10 hours.